000			02017ntdaa2200385 ab4500
003			UnInEc
005			20231213110845.0
006			a||||g ||i| 00| 0
008			140501s9999 mx ||||f |||| 00| 0 spa d
020			_a9780195115383
040			_aCIBESPAM MFL
041			_aeng
082			_a310 _bG659 _c1997
100			_aGoovaerts, Pierre
245			_aGeostatistics for natural resources evaluation.
260			_aUnited States of America _bOxford University Press _c1997
300			_axiv, 483 páginas; _btable, figures, grafico; _c 24 cm x 16.5 cm
490			_aApplied geostatistics
505			_a1. Introduction 2. Exploratory Data Analysis 3. The Random Function Model 4. Inference and Modeling 5. Local Estimation: Accounting for a Single Attribute 6. Local Estimation: Accounting for Secondary Information 7. Assessment of Local Uncertainty 8. Assessment of Spatial Uncertainty 9. Summary
520			_aThis text fulfills a need for an advanced-level work covering both the theory and application of geostatistics. It covers the most important areas of geostatistical methodology, introducing tools for description, quantitative modeling of spatial continuity, spatial prediction, and assessment of local uncertainty and stochastic simulation. It also details the theoretical background underlying most GSLIB programs. The tools are applied to an environmental data set, but the book includes a general presentation of algorithms intended for students and practitioners in such diverse fields as soil science, mining, petroleum, remote sensing, hydrogeology, and the environmental sciences.
650			_aUnivariate
650			_aLocation
650			_aMeasures
650			_aCategorical
650			_aSpatial
650			_aRandom variable
650			_aOptimal
650			_aEstimation
650			_aSimulation
650			_aAnisotropic
650			_aIndicator
912			_c2023-12-13 _dMaría Zambrano
913			_aFNME _bCIA _dGARNB
942			_2ddc _cBK
999			_c12996 _d12996